Connection to the reinforcement learning the goal is development of such algorithms which is capable efficiently solving of larger problems too. The proximately optimal results also can be mean great progress in case of many tasks as compared to realized efficiency by the heuristic, ad hoc results. We would like to use the data of log files to the solving of tasks, which derives from execution of processes. We can increase charge efficiency by the explored of hidden information.
The goal of research is development of such processes based on reinforcement learning and process mining, which suits solving of bin packing and scheduling problems. The goal is reducing of the execution time and/or the cost of the bin packing, respectively the technologic process. Another topic of the research is development of efficient metaheuristics to preceding tasks. The composed tools and methods will be apply for different type of tasks considering characteristics of the application area.